activity
20142020
most citedKernel Least Mean Square with Adaptive Kernel Size

105 citations · 171 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SP2020★ 1 cited

Neurodynamic TDOA localization with NLOS mitigation via maximum correntropy criterion

Wenxin Xiong, Christian Schindelhauer, Hing Cheung So +2

In this paper, we exploit the maximum correntropy criterion (MCC) to robustify the traditional time-difference-of-arrival (TDOA) location estimator in the presence of non-line-of-s…

eess.SP2020★ 60 cited

TDOA-based localization with NLOS mitigation via robust model transformation and neurodynamic optimization

Wenxin Xiong, Christian Schindelhauer, Hing Cheung So +3

This paper revisits the problem of locating a signal-emitting source from time-difference-of-arrival (TDOA) measurements under non-line-of-sight (NLOS) propagation. Many currently…

math.NA2019★ 3 cited

Accelerated Symmetric ADMM and Its Applications in Signal Processing

Jianchao Bai, Junli Liang, Ke Guo +1

The alternating direction method of multipliers (ADMM) were extensively investigated in the past decades for solving separable convex optimization problems. Fewer researchers focus…

eess.IV2018

Robust Real-time Ellipse Fitting Based on Lagrange Programming Neural Network and Locally Competitive Algorithm

Hao Wang, Chi-Sing Leung, Hing Cheung So +3

Given a set of 2-dimensional (2-D) scattering points, which are usually obtained from the edge detection process, the aim of ellipse fitting is to construct an elliptic equation th…

eess.SP2018★ 2 cited

Robust MIMO Radar Target Localization based on Lagrange Programming Neural Network

Hao Wang, Chi-Sing Leung, Hing Cheung So +3

This paper focuses on target localization in a widely distributed multiple-input-multiple-output (MIMO) radar system. In this system, range measurements, which include the sum of d…

stat.ML2014★ 105 cited

Kernel Least Mean Square with Adaptive Kernel Size

Badong Chen, Junli Liang, Nanning Zheng +1

Kernel adaptive filters (KAF) are a class of powerful nonlinear filters developed in Reproducing Kernel Hilbert Space (RKHS). The Gaussian kernel is usually the default kernel in K…